Legal case summarization is an important problem, and several domain-specific summarization algorithms have been applied for this task. These algorithms generally use domain-specific legal dictionaries to estimate the importance of sentences. However, none of the popular summarization algorithms use document-specific catchphrases, which provide a unique amalgamation of domain-specific and document-specific information. In this work, we assess the performance of two legal document summarization algorithms, when two different types of catchphrases are incorporated in the summarization process. Our experiments confirm that both the summarization algorithms show improvement across all performance metrics, with the incorporation of document-specific catchphrases.